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Prerequisites

The potential candidates should have 12-24 months of experience in architecting, developing, or running machine learning or deep learning workloads particularly on AWS Cloud. They must also possess the ability to effectively express the intuition behind basic machine learning algorithms. It is also advisable to have some experience with machine learning and deep learning frameworks, as well as be able to follow operational & deployment best practices.

AWS Certified Machine Learning – Specialty is a standard exam for candidates who want to excel in the development field and data science and verify their competence by earning certification. This test, coded MLS-C01, helps the individuals to measure their knowledge of the design, deployment, implementation, and maintenance of machine learning solutions.

This exam allows candidates to validate their skills related to choosing the right AWS services for Machine learning implementation and resolving business problems. Also, they prove their ability to create reliable, cost effective, and secure ML solutions.

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Understanding functional and technical aspects of AWS Certified Machine Learning Specialty Exam Machine Learning Implementation and Operations

The following will be dicussed here:

• Deploy and operationalize machine learning solutions
• Build machine learning solutions for performance, availability, scalability, resiliency, and fault tolerance
• Recommend and implement the appropriate machine learning services and features for a given problem
• Apply basic AWS security practices to machine learning solutions

Reference: https://d1.awsstatic.com/training-and-certification/docs-ml/AWS%20Certified%20Machine%20Learning%20-%20Specialty_Exam%20Guide%20(1).pdf

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